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Outcome of allogeneic stem cell transplantation (alloSCT) is hampered by substantial non-relapse mortality (NRM). Given its impact on organ function and immune response, the nutritional status has been suggested as relevant for NRM. We aimed to evaluate the association of NRM with nutritional status prior to alloSCT and in the post-SCT course. In a retrospective single-center study, we analyzed 128 alloSCTs. Besides standard characteristics, nutrition-associated parameters BMI, serum total protein, and serum albumin were recorded before conditioning and at various time points after alloSCT. Association with NRM was evaluated by univariate and multivariate survival analysis. The cohort comprised patients with a median BMI of 26 kg/m2 (16.7-46.9 kg/m2), median serum total protein of 59 g/l (41-77 g/l), and serum albumin of 36 g/l (22-46 g/l) before SCT. NRM at d+100 was 14.8% and at 1 year 26.6%. Prior to SCT, only serum albumin deficiency was associated with increased NRM (p = .010) in multivariate analysis. After SCT (d+30 and d+100), all nutrition-associated parameters decreased (p < .002), but no association of deteriorating nutritional status with NRM was found. In multivariate analysis, serum albumin (p = .03) and severe albumin deficiency (p = .02) correlated with NRM at d+30 and d+100, while BMI and serum total protein did not. In our study, albumin deficiency, particularly prior to alloSCT, shows a strong correlation with NRM. This finding may add to monitoring, risk evaluation, and counseling of patients and serve as a rational for interventions to improve the nutritional status in patients undergoing SCT.

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BACKGROUND: Restrained Eating, i.e. the tendency to restrict dietary intake to control body-weight, often emerges during adolescence and may result in changes in circadian eating patterns. OBJECTIVE: The objective of the present investigation was to determine the cross-sectional relevance of restrained eating for characteristics of circadian eating pattern in adolescents and whether changes in restrained eating are accompanied by concurrent changes in circadian eating pattern over the course of adolescence. METHODS: Two questionnaires assessing restrained eating (Score 0-30) with parallel 3-day weighed dietary records from two different time points were available from 209 (♂:101, ♀:108) 11-18 year old adolescents of the DONALD study. Mixed linear regression models were used to analyze whether restrained eating was associated with eating occasion frequency, snack frequency and morning and evening energy intake [in % of daily energy intake, %E]. Linear regression models were used to examine whether changes in restrained eating were associated with changes in the mentioned variables. RESULTS: Among girls, greater restrained eating was cross-sectionally associated with higher morning energy intake (p = 0.03). Further, there was a tendency towards lower evening energy intake with higher levels of restrained eating for the whole sample (p = 0.06). No cross-sectional associations were found with eating occasion or snack frequency. Each one-point increase in restrained eating during adolescence was related to a concurrent decrease in eating occasion frequency by 0.04 (95% CI -0.08; -0.01, p = 0.02) and in evening energy intake by 0.36%E (95% CI -0.70; -0.03, p = 0.04). A tendency towards decreasing snack frequency with increasing restrained eating was observed (ß = -0.03, 95% CI -0.07; 0.00, p = 0.07). No association was found between changes in restrained eating and concurrent changes in morning energy intake. CONCLUSION: We found indications for cross-sectional and prospective associations between restrained eating and chronobiological aspects of food intake in adolescents. Our results suggest that restrained eating should be considered a relevant determinant of circadian eating patterns.

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The present manuscript addressed two hypotheses: (i) As children age, energy intake is shifted from morning (energy intake <11am) to evening hours (energy intake >6pm) (ii) A higher 'eveningness in energy intake' (i.e. evening minus morning energy intake) is associated with a higher total daily energy intake. Data were analyzed from 262 DONALD cohort study participants, who had completed at least one 3-day weighed dietary record in the age groups 3/4, 5/6, 7/8, 9/10, 11/12, 13/14, 15/16 and 17/18 years (y). 'Eveningness in energy intake' was compared across age groups and related to total daily energy intake for each age group (multiple cross-sectional analyses). 'Eveningness' increased progressively from age group 3/4y to age group 17/18y. A median surplus of evening energy intake (i.e. when evening intake exceeded morning intake) was firstly observed for age group 11/12y. From age group 11/12y onwards, a higher 'eveningness' was associated with a higher total daily energy intake (all p < 0.04). Difference in total daily energy intake between the highest and the lowest tertile of 'eveningness' was largest for age group 17/18y, amounting to an 11% higher intake among adolescents in the highest as compared to those in the lowest tertile. In conclusion, energy intake progressively shifts from morning to evening hours as children age. Once evening energy intake exceeds morning energy intake, a higher 'eveningness in energy intake' is associated with higher total daily energy intake.

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The present study describes time and age trends in morning and evening protein intakes and sources among German children and adolescents from 1985 to 2014. A total of 9757 three-day weighed dietary records of 1246 3- to 18-year-old participants of the Dortmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study were analysed using polynomial mixed-effects regression models. Morning protein intake increased over the study period by approximately 1 % of morning energy intake (linear trend P < 0·0001), with the youngest and the oldest children having the highest protein intake (linear, quadratic trend P < 0·0001). Evening protein intake increased over time by approximately 2 % of evening energy intake in girls (linear trend P < 0·0001) and 1 % of evening energy intake in boys (quadratic trend P = 0·0313), with decreasing intake with age (girls: linear trend P < 0·0001; boys: linear trend P = 0·0963). Time trends were largely due to increases in protein from 'starchy foods'. In conclusion, morning and evening protein intakes increased modestly between 1985 and 2014; these increases were, however, not accompanied by increases in traditional protein sources (i.e. meat or dairy products).

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During adolescence, a shift from morningness to eveningness occurs, yet school continues to start early in the morning. Hence, adolescents are at risk for social jetlag, i.e. a discrepancy between biological and social timing. It remains to be determined whether chronotype associates with daily and daytime-specific eating patterns during this potentially critical period. Therefore, the aim of the present study was to investigate whether chronotype is decisive for daily eating patterns [total energy intake (TEI, kcal), total macronutrient intake (% of TEI), eating occasion frequency (n/day), meal frequency (n/day), snack frequency (n/day), duration of nightly fasting], or daytime-specific eating patterns [morning (before 11 am) energy intake (% of TEI), morning macronutrient intake (% of morning energy intake), regular breakfast skipping (no morning energy intake at least on 2 of 3 days, yes/no), evening (after 6 pm) energy intake (% of TEI), evening macronutrient intake (% of evening energy intake), regular dinner skipping (no evening energy intake at least on 2 of 3 days, yes/no)] in German adolescents. Chronotype was assessed by use of the Munich Chronotype Questionnaire and is defined as the midpoint of sleep corrected for sleep-debt accumulated over the workweek (the later the midpoint of sleep, the later the chronotype). A total of 223 participants (10-18 years) provided 346 questionnaires and concurrent 3-day weighed dietary records. Associations between chronotype and eating patterns were analyzed cross-sectionally using multivariable linear and logistic mixed-effects regression models. Adolescents with earlier and later chronotypes did not differ in their daily eating patterns. With respect to daytime-specific eating patterns, 1 h delay in chronotype was associated with 4.0 (95% CI 2.5-6.6) greater odds of regular breakfast skipping (p < 0.0001). In addition, later chronotype was associated with higher evening energy intake (p = 0.0009). In conclusion, our data show that a later chronotype among adolescents is associated with a shift of food consumption toward later times of the day. Hence, adolescents' eating patterns appear to follow their internal clock rather than socially determined schedules.

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BACKGROUND: This study investigated whether glycemic index (GI) or glycemic load (GL) of morning or evening intake and morning or evening carbohydrate intake from low- or higher-GI food sources (low-GI-CHO, higher-GI-CHO) during adolescence are relevant for risk markers of type 2 diabetes in young adulthood. Methods: Analyses included DOrtmund Nutritional and Anthropometric Longitudinally Designed (DONALD) study participants who had provided at least two 3-day weighed dietary records (median: 7 records) during adolescence and one blood sample in young adulthood. Using multivariable linear regression analyses, estimated morning and evening GI, GL, low-GI-CHO (GI < 55) and higher-GI-CHO (GI ≥ 55) were related to insulin sensitivity (N = 252), hepatic steatosis index (HSI), fatty liver index (FLI) (both N = 253), and a pro-inflammatory-score (N = 249). Results: Morning intakes during adolescence were not associated with any of the adult risk markers. A higher evening GI during adolescence was related to an increased HSI in young adulthood (p = 0.003). A higher consumption of higher-GI-CHO in the evening was associated with lower insulin sensitivity (p = 0.046) and an increased HSI (p = 0.006), while a higher evening intake of low-GI-CHO was related to a lower HSI (p = 0.009). Evening intakes were not related to FLI or the pro-inflammatory-score (all p > 0.1). Conclusion: Avoidance of large amounts of carbohydrates from higher-GI sources in the evening should be considered in preventive strategies to reduce the risk of type 2 diabetes in adulthood.

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PURPOSE: To describe age and time trends in eating occasion frequency (EOF), meal frequency (MF), snack frequency (SF) and duration of nightly fasting (DNF) in German children and adolescents. METHODS: 9757 3-day dietary records of 1246 3-18-year-old participants of the open DONALD cohort study, collected 1985-2014, were analyzed for age and time trends using polynomial mixed-effects regression models. Eating occasions were either assigned to meals or snacks (>10 or ≤10 % of daily total energy intake per eating occasion). DNF was defined as the longest time span without energy intake within one night. RESULTS: EOF, MF and SF decreased with age (EOF: linear, quadratic, cubic trend p < 0.0001; MF: linear trend p < 0.0001; SF: linear, quadratic trend p < 0.0001). Time trend analyses revealed a wavelike time course for EOF (linear trend p = 0.0580, quadratic trend = 0.0039, cubic trend = 0.0015) and SF (linear trend p = 0.0055, quadratic trend p = 0.0005, cubic trend p = 0.0003). MF slightly increased until 2000 and decreased thereafter (linear trend p = 0.0012, quadratic trend p = 0.0047). Effect sizes of time trends in EOF, MF and SF were small. Boys' and girls' DNF decreased with age (in both: linear, quadratic, cubic trend p < 0.0001) and increased over the study period (boys: linear trend p = 0.0011, interaction of age and time p < 0.0001; girls: linear trend p = 0.0167). CONCLUSION: EOF, MF and SF were higher in children than in adolescents, but, in contrast to other studies remained fairly stable over the study period. Decreasing DNF with age could reflect decreasing sleep durations. Additionally, DNF increased over the study period, probably due to an increase in breakfast skipping.

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(1) Background: This study investigated the relevance of morning and evening energy and macronutrient intake during childhood for body composition in early adolescence; (2) Methods: Analyses were based on data from 372 DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed study) participants. Explorative life-course plots were performed to examine whether morning or evening energy and macronutrient intake at 3/4 years, 5/6 years, or 7/8 years is critical for fat mass index (FMI [kg/m²]) and fat free mass index (FFMI [kg/m²]) in early adolescence (10/11 years). Subsequently, exposures in periods identified as consistently critical were examined in depth using adjusted regression models; (3) Results: Life-course plots identified morning fat and carbohydrate (CHO) intake at 3/4 years and 7/8 years as well as changes in these intakes between 3/4 years and 7/8 years as potentially critical for FMI at 10/11 years. Adjusted regression models corroborated higher FMI values at 10/11 years among those who had consumed less fat (p = 0.01) and more CHO (p = 0.01) in the morning at 7/8 years as well as among those who had decreased their morning fat intake (p = 0.02) and increased their morning CHO intake (p = 0.05) between 3/4 years and 7/8 years; (4) Conclusion: During childhood, adherence to a low fat, high CHO intake in the morning may have unfavorable consequences for FMI in early adolescence.

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